class_docstr: Implementations of DRL algorithms
  Attributes
  ----------
      env: gym environment class
          user-defined class
  Methods
  -------
      get_model()
          setup DRL algorithms
      train_model()
          train DRL algorithms in a train dataset
          and output the trained model
      DRL_prediction()
          make a prediction in a test dataset and get results
code: def train_model(self, model, cwd, total_timesteps=5000):
      model.cwd = cwd
      model.break_step = total_timesteps
      train_agent(model)
  
file_path: FinRL/finrl/agents/elegantrl/models.py
imports: from __future__ import annotations
  import torch
  from elegantrl.agents import *
  from elegantrl.train.config import Config
  from elegantrl.train.run import train_agent
label_desc: Use image node_id 3 for calling the DRLAgent obj's underlying member method code with example usage: obj.train_model(model, cwd, total_timesteps) without return types